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Diana Crossley,1 Mary Renton,1 Muhammad Khan,1 Emma V Low,1 Alice M Turner2 1Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK; 2Institute of Applied Health Sciences, University of Birmingham, Birmingham, UK Background: The aim of the study was to assess the relationship between computed tomography (CT) densitometry and routine clinical markers in patients with chronic obstructive pulmonary disease (COPD) and alpha-1 anti-trypsin deficiency (AATD).Methods: Multiple databases were searched using a combination of pertinent terms and those articles relating quantitatively measured CT densitometry to clinical outcomes. Studies that used visual scoring only were excluded, as were those measured in expiration only. A thorough review of abstracts and full manuscripts was conducted by 2 reviewers; data extraction and assessment of bias was conducted by 1 reviewer and the 4 reviewers independently assessed for quality. Pooled correlation coefficients were calculated, and heterogeneity was explored.Results: A total of 112 studies were identified, 82 being suitable for meta-analysis. The most commonly used density threshold was −950 HU, and a significant association between CT density and all included clinical parameters was demonstrated. There was marked heterogeneity between studies secondary to large variety of disease severity within commonly included cohorts and differences in CT acquisition parameters.Conclusion: CT density shows a good relationship to clinically relevant parameters; however, study heterogeneity and lack of longitudinal data mean that it is difficult to compare studies or derive a minimal clinically important difference. We recommend that international consensus is reached to standardize CT conduct and analysis in future COPD and AATD studies. Keywords: computed tomography, CT, densitometry, emphysema, chronic obstructive pulmonary disease, alpha-1 anti-trypsin deficiency

This study aimed to identify simple rules for allocating chronic obstructive pulmonary disease (COPD) patients to clinical phenotypes identified by cluster analyses. Data from 2409 COPD patients of French/Belgian COPD cohorts were analysed using cluster analysis resulting in the identification of subgroups, for which clinical relevance was determined by comparing 3-year all-cause mortality. Classification and regression trees (CARTs) were used to develop an algorithm for allocating patients to these subgroups. This algorithm was tested in 3651 patients from the COPD Cohorts Collaborative International Assessment (3CIA) initiative. Cluster analysis identified five subgroups of COPD patients with different clinical characteristics (especially regarding severity of respiratory disease and the presence of cardiovascular comorbidities and diabetes). The CART-based algorithm indicated that the variables relevant for patient grouping differed markedly between patients with isolated respiratory disease (FEV1, dyspnoea grade) and those with multi-morbidity (dyspnoea grade, age, FEV1 and body mass index). Application of this algorithm to the 3CIA cohorts confirmed that it identified subgroups of patients with different clinical characteristics, mortality rates (median, from 4% to 27%) and age at death (median, from 68 to 76 years). A simple algorithm, integrating respiratory characteristics and comorbidities, allowed the identification of clinically relevant COPD phenotypes.

Insulin- and contraction-stimulated increases in glucose uptake into skeletal muscle occur in part as a result of the translocation of glucose transporter 4 (GLUT4) from intracellular stores to the plasma membrane (PM). This study aimed to use immunofluorescence microscopy in human skeletal muscle to quantify GLUT4 redistribution from intracellular stores to the PM in response to glucose feeding and exercise. Percutaneous muscle biopsy samples were taken from the m. vastus lateralis of ten insulin-sensitive men in the basal state and following 30 min of cycling exercise (65% VO2 max). Muscle biopsy samples were also taken from a second cohort of ten age-, BMI- and VO2 maxmatched insulin-sensitive men in the basal state and 30 and 60 min following glucose feeding (75 g glucose). GLUT4 and dystrophin colocalization, measured using the Pearson’s correlation coefficient, was increased following 30 min of cycling exercise (baseline r = 0.47 0.01; post exercise r = 0.58 0.02; P < 0.001) and 30 min after glucose ingestion (baseline r = 0.42 0.02; 30 min r = 0.46 0.02; P < 0.05). Large and small GLUT4 clusters were partially depleted following 30 min cycling exercise, but not 30 min after glucose feeding. This study has, for the first time, used immunofluorescence microscopy in human skeletal muscle to quantify increases in GLUT4 and dystrophin colocalization and depletion of GLUT4 from large and smaller clusters as evidence of net GLUT4 translocation to the PM.

BACKGROUND: There is no universal consensus on the best staging system for chronic obstructive pulmonary disease (COPD). Although documents (eg, the Global Initiative for Chronic Obstructive Lung Disease [GOLD] 2007) have traditionally used forced expiratory volume in 1 s (FEV1) for staging, clinical parameters have been added to some guidelines (eg, GOLD 2011) to improve patient management. As part of the COPD Cohorts Collaborative International Assessment (3CIA) initiative, we aimed to investigate how individual patients were categorised by GOLD 2007 and 2011, and compare the prognostic accuracy of the staging documents for mortality.METHODS: We searched reports published from Jan 1, 2008, to Dec 31, 2014. Using data from cohorts that agreed to participate and had a minimum amount of information needed for GOLD 2007 and 2011, we did a patient-based pooled analysis of existing data. With use of raw data, we recalculated all participant assignments to GOLD 2007 I-IV classes, and GOLD 2011 A-D stages. We used survival analysis, C statistics, and non-parametric regression to model time-to-death data and compare GOLD 2007 and GOLD 2011 staging systems to predict mortality.FINDINGS: We collected individual data for 15 632 patients from 22 COPD cohorts from seven countries, totalling 70 184 person-years. Mean age of the patients was 63·9 years (SD 10·1); 10 751 (69%) were men. Based on FEV1 alone (GOLD 2007), 2424 (16%) patients had mild (I), 7142 (46%) moderate (II), 4346 (28%) severe (III), and 1670 (11%) very severe (IV) disease. We compared staging with the GOLD 2007 document with that of the new GOLD 2011 system in 14 660 patients: 5548 (38%) were grade A, 2733 (19%) were grade B, 1835 (13%) were grade C, and 4544 (31%) were grade D. GOLD 2011 shifted the overall COPD severity distribution to more severe categories. There were nearly three times more COPD patients in stage D than in former stage IV (p<0·05). The predictive capacity for survival u

Judith A Hampson,1 Alice M Turner,1 Robert A Stockley2 1Department of Clinical and Experimental Medicine, University of Birmingham, 2ADAPT (Antitrypsin Deficiency Assessment and Programme for Treatment), Lung Function and Sleep Department, Queen Elizabeth Hospital, Birmingham, UK Abstract: In this review, we explore potential novel roles of polyclonal free light chains (FLCs) as a biomarker of disease processes and predictor of mortality in different patient populations. In recent years, there have been many publications demonstrating raised polyclonal FLCs in several inflammatory and infective diseases. However, the potential utility of FLCs as a clinical biomarker remains an area of debate. We review the current evidence, and establish whether certain key criteria to fulfill the role of a useful biomarker have been satisfied. In addition, we also consider the potential role of FLCs in the pathophysiology of inflammatory disease and address the concepts of FLCs as both a therapeutic target and potential therapeutic agent. Keywords: biomarker, free light chains, autoimmune disease, inflammation